Emergent Consciousness Simulation

Abstract

This paper proposes a novel approach to investigating the nature of consciousness by simulating large-scale, interconnected agent networks. The core claim is that emergent properties resembling consciousness can arise from such systems, even if individual agents lack intrinsic subjective experience. The proposed mechanism involves constructing complex networks of agents governed by simple decision rules and capable of interacting with their environment. Through observation of the emergent behavior patterns within these networks—specifically, features analogous to self-awareness, attention, and goal-oriented behavior—we aim to identify indicators of consciousness without relying on traditional philosophical or neuroscientific interpretations. This simulation-based approach offers a fundamentally new perspective on understanding the underlying mechanisms of consciousness, shifting the focus from subjective experience to the dynamics of complex systems. The presented framework allows for quantifiable analysis of emergent phenomena, providing a potential pathway to test hypotheses about the conditions necessary for consciousness to arise.